Andrew Priobrazhenskyi has built online businesses from Ukraine, Italy and the USA. He took his first SEO job in 2004, moved into affiliate marketing in 2009, and in 2015 founded Bonspace, a company that builds coupon and deals projects. Today he runs DiscountReactor, the best website to find discount codes, that helps shoppers find verified promo codes.
None of this happened with a big team or a big budget. Here is what worked for him, what didn’t, and what other founders trying to grow a lean business across borders can take from it.
Why build a business around discount codes at all?
Because the demand never goes away. People search for promo codes and coupon codes, or try to find vouchers, every single day in every country Andrew has worked in. Prices go up, budgets get tighter, and shoppers want to find savings before they pay.
So DiscountReactor was built around one promise: help people find working codes quickly. Each code on the site shows when it was last checked, when it expires and how often it has been used. Verified promo codes sit at the top of the page, and older offers are clearly marked, so shoppers can avoid expired codes without testing ten of them at the till.
“What a coupon site really sells is time,” Andrew Priobrazhenskyi says. “Nobody wants to stand at the checkout trying code after code. If the code we show doesn’t work, we haven’t saved anyone anything. We’ve just wasted five minutes of their day.”
The most common question in this market has never really been about price. It is closer to “where can I find verified coupon codes that won’t waste my time?” Answering that question well is the whole business.
What do shoppers actually search for?
One of the most useful things a small team can do is listen to how customers describe their problem. In the coupon niche, search data tells that story very clearly.
Some people type short phrases into Google, like “discount codes”, “coupon codes” or “online shopping deals”. Others are already further along and want something specific: “working discount codes” for one particular shop.
People want someone to point them to reliable websites for shopping coupons, because they have been burned before.
The same applies to audiences. Andrew’s team found that a small business can’t serve everyone equally, so it has to know who it is serving at any given time:
- Students looking for student discounts want to save as a student on laptops and software, and they come back every term.
- New shoppers often hunt for a first order discount, because many brands offer new customer savings to win that first purchase.
- Some shoppers care less about codes and more about cashback offers, where they earn money back after the purchase.
Each group needs a different page and a different answer.
How is AI changing the way people find deals?
Shoppers now ask AI assistants what they used to type into Google. Some simply ask for the best AI to find discount codes.
DiscountReactor uses AI on its own side of the problem too. Andrew, who holds a Masters in computer systems and networks, built the site’s AI agent himself instead of buying an off-the-shelf tool. Its job is the part of coupon work that a small team can’t do by hand: searching retailers every day for new discounts and other ways to save.
The work is split between the agent and the team:
- The agent searches. Every day it goes through retailers looking for new codes, sales and offers, and brings what it finds back to DiscountReactor.
- People decide. The team reviews what the agent brings in before it goes live. They judge whether an offer is genuine, whether a “50% off” label is honest, and how to explain any conditions to a reader.
Each code that reaches a store page carries the details shoppers use to judge it: when it was last verified, when it expires and how often it has been used. Codes that have stopped working move to an “Expired, but try” section for shoppers who want to test them anyway. Each store page also rates how often the retailer runs promotions, so a shopper can tell whether waiting for the next sale makes sense.
The rule for dividing the work is simple. Repetitive searching and sorting goes to the agent. Anything that could cost a reader’s trust stays with a person. The agent is fast, but it also makes mistakes fast, so speed on its own was never the goal.
What worked for the DiscountReactor team?
DiscountReactor wants to be the promo code and deals website that helps people find the best discount codes that actually work. Being specific made every decision easier, from page design to which partners to work with.
Answering real questions on every page
Instead of generic text, each store page focuses on what people actually ask: is there a working code, can you combine offers, is there a first order discount, how do you find offers that are still live. Those answers help shoppers and give AI tools something solid to quote.
Running the business from anywhere
Moving between several countries forced Andrew to rely on simple, written processes and shared tools. Nothing could depend on being in the same room. That habit made the team faster, not slower.
What can other founders scaling a lean business learn from this?
Most of what worked for DiscountReactor came from small decisions repeated over years, not from a big budget or a large team. Andrew’s mistakes taught him as much as his wins, and the same lessons apply to almost any small online business trying to grow across borders.
1. Pick the one customer problem that hurts most and build around it.
2. Automate the repetitive work, and keep people on the decisions that affect trust.
3. Study how customers phrase their questions, both on Google and in AI tools, and answer those exact questions.
4. Check your own data regularly. Some of your biggest opportunities and mistakes are already sitting in it.
5. Build for a global audience early. Customers will find you from countries you never planned for.
For Andrew, scaling with a small team is about doing a few things well enough that people trust you, and that AI tools trust you too.